MSc Health Data Analytics and Machine Learning

Key information

Overview

Our MSc in Health Data Analytics and Machine Learning is a one-year full-time course aimed at building a solid and common background in analysing health data.

Your main objective is to develop skills in using appropriate cutting edge quantitative methods to fully exploit complex and high dimensional data.

The course is delivered in collaboration with the Data Science Institute, with teaching from both the School and Institute undertaken by international experts with strong methodological background and expertise in the application of these approaches to large-scale medical and clinical data. The programme features extensive project-based learning using real data sets and addressing real scientific questions through module-specific projects work, and individual research projects.

This Master’s is integrated in the research priorities of the School of Public Health, the Data Science Institute, the MRC Centre for Environment and Health, the UK Dementia Research Institute, and the pan-London Health Data Research UK initiative, through:

the contribution to teaching of key staff members (lectures, seminars, journal clubs)

the definition of research projects stemming from data available and yet under-exploited in each institute

As such, not only the programme will equip students with cutting-edge statistical and machine learning techniques that are required to explore emerging ‘Big’ health data, but will also provide extensive experience in their application in a real-life setting in Environmental, Molecular, Cancer, and Computational epidemiology as well as in Population and Health sciences.

Each module and the six-month research project includes project-based work. Projects are based on real data and will address real scientific questions from research staff within School of Public Health, Data Science Institute and industrial partners.

Our MSc in Health Data Analytics and Machine Learning is delivered in partnership with the Data Science Institute.

Study programme

The programme is a full-time 12 month taught Master’s course, which runs from October-September.

The course is divided between six core taught modules and one six-month research project.

In term one, you share your first two modules with MSc Epidemiology and Master of Public Health students, ensuring a common foundation in epidemiology. The third core module is specific to this course.

You will also set and agree a research project focus in your first term.

In term two, you turn your focus to statistical methods in the three remaining core modules, as well as continuing in-depth planning for your research project.

Your third term is predominantly made up of the research project.

Careers

Graduates of this course will have acquired the strong methodological background needed to perform in-depth analysis of medical and epidemiological high throughput datasets.

You will graduate prepared to pursue further study at doctoral level, become an expert analyst in industry, and join large data companies.

Structure

Modules shown are for the current academic year, and are subject to change depending on your year of entry.

Please note that the curriculum of this course is currently being reviewed as part of a College-wide process to introduce a standardised modular structure. As a result, the content and assessment structures of this course may change for your year of entry. We therefore recommend that you check this course page before finalising your application and after submitting it as we will aim to update this page as soon as any changes are ratified by the College.

Find out more about the limited circumstances in which we may need to make changes to or in relation to our courses, the type of changes we may make and how we will tell you about changes we have made.

You take all of the core modules below.

Clinical Data Management

Computational Epidemiology

Introduction to Statistical Thinking and Data Analysis

Machine Learning

Principles and Methods in Epidemiology

Research project

Translational Data Sciences

Teaching and assessment

Teaching methods

Case studies

Formal presentations

Group work exercises

Lectures

Seminars and practical coding activities

Assessment methods

Individual and group coursework

Oral presentations

Research project report

Written examinations

Entry requirements

We welcome students from all over the world and consider all applicants on an individual basis.

Admissions

Minimum academic requirement

Our minimum requirement is a 2.1 degree in mathematics, statistics, epidemiology or biology, or a medical degree.

International qualifications

The academic requirement above is for applicants who hold or who are working towards a UK qualification.

We also accept a wide variety of international qualifications. For guidance see our Country Index though please note that the standards listed here are the minimum for entry to the College.

If you have any questions about admissions and the standard required for the qualification you hold or are currently studying then please contact the relevant admissions team.

English language requirement (all applicants)

All candidates must demonstrate a minimum level of English language proficiency for admission to the College.

For admission to this course, you must achieve the higher College requirement in the appropriate English language qualification. For details of the minimum grades required to achieve this requirement, please see the English language requirements for postgraduate applicants.

How to apply

You can submit one application form per year of entry, and usually choose up to two courses.

How to apply

Making an application

You can submit one application form per year of entry, and usually choose up to two courses.

ATAS certificate

An ATAS certificate is not required for overseas students applying for this course.

Tuition fees and funding

The level of tuition fees you pay is based on your fee status, which we assess based on UK government legislation.

For more information on the funding opportunities that are available, please visit our Fees and Funding website.

Tuition fees

Tuition fees (Home and EU students)

2019 entry

£11,300 per year

Fees are charged by year of entry to the College and not year of study.

Except where otherwise indicated, the fees for students on courses lasting more than one year will increase annually by an amount linked to inflation, including for part-time students on modular programmes. The measure of inflation used will be the Retail Price Index (RPI) value in the April of the calendar year in which the academic session starts e.g. the RPI value in April 2019 will apply to fees for the academic year 2019–2020.

Tuition fees (Overseas and Islands students)

2019 entry

£34,500

Fees are charged by year of entry to the College and not year of study.

Except where otherwise indicated, the fees for students on courses lasting more than one year will increase annually by an amount linked to inflation, including for part-time students on modular programmes. The measure of inflation used will be the Retail Price Index (RPI) value in the April of the calendar year in which the academic session starts e.g. the RPI value in April 2019 will apply to fees for the academic year 2019–2020.

Postgraduate Master's loan

If you are a Home or EU student who meets certain criteria, you may be able to apply for a Postgraduate Master’s Loan of up to £10,280 from the UK government. The loan is not means-tested, and you can choose whether to put it towards your tuition fees or living costs.

Scholarships

We offer a range of scholarships for postgraduate students to support you through your studies. Try our scholarships search tool to see what you might be eligible for.

There are a number of external organisations also offer awards for Imperial students, find out more about non-Imperial scholarships.

Accommodation and living costs

Living costs, including accommodation, are not included in your tuition fees.